Co-expression network analysis identifies potential candidate hub genes in severe influenza patients needing invasive mechanical ventilation

Abstract

Background Influenza is a contagious disease that affects people of all ages and is linked to considerable mortality during epidemics and occasional outbreaks. Moreover, effective immunological biomarkers are needed for elucidating aetiology and preventing and treating severe influenza. Herein, we aimed to evaluate the key genes linked with the disease severity in influenza patients needing invasive mechanical ventilation (IMV). Three gene microarray data sets (GSE101702, GSE21802, and GSE111368) from blood samples of influenza patients were made available by the Gene Expression Omnibus (GEO) database. The GSE101702 and GSE21802 data sets were combined to create the training set. Hub indicators for IMV patients with severe influenza were determined using differential expression analysis and Weighted correlation network analysis (WGCNA) from the training set. The receiver operating characteristic curve (ROC) was also used to evaluate the hub genes from the test set's diagnostic accuracy. Different immune cells' infiltration levels in the expression profile and their correlation with hub gene markers were examined using single-sample gene set enrichment analysis (ssGSEA). Results In the present study, we evaluated a total of 447 differential genes. WGCNA identified eight co-expression modules, with the red module having the strongest correlation with IMV patients. Differential genes were combined to obtain 3 hub genes (HLA-DPA1, HLA-DRB3, and CECR1). The identified genes were investigated as potential indicators for patients with severe influenza who required IMV using the least absolute shrinkage and selection operator (LASSO) approach. The ROC showed the diagnostic value of the three hub genes in determining the severity of influenza. Using ssGSEA, it has been revealed that the expression of key genes was negatively correlated with neutrophil activation and positively associated with adaptive cellular immune response. Conclusion We evaluated three novel hub genes that could be linked to the immunopathological mechanism of severe influenza patients who require IMV treatment and could be used as potential biomarkers for severe influenza prevention and treatment.

Linked Mutations in the Ebola Virus Polymerase Are Associated with Organ Specific Phenotypes

“…Using WGCNA, we identified Hub genes of the modules with a negative/positive correlation to the days of postinfection. Hub genes are the genes with high correlation in candidate modules, expected to provide potential targets for diagnosis and treatment ( 27 ), especially the Hub genes in the virus defense and immune response modules ( Fig. 8 ; Table 3 ).…”

The novel HLA‐DPA1*02:86 allele was identified by next‐generation sequencing

“…It was reported that the HLA‐DPA1 gene may play a key role in the immune‐pathological condition of severe influenza 1 . Compared with the HLA‐DPB1 locus, HLA‐DPA1 gene has limited polymorphism with a smaller number of reported HLA‐DPA1 alleles 2 .…”

“…It was reported that the HLA-DPA1 gene may play a key role in the immune-pathological condition of severe influenza. 1 Compared with the HLA-DPB1 locus, HLA-DPA1 gene has limited polymorphism with a smaller number of reported HLA-DPA1 alleles. 2 According to the 3.55.0 version of IPD-IMGT/HLA Database, more than 639 HLA-DPA1 alleles have been identified.…”